After algorithmic recommendation technology is deeply embedded in cyberspace, the targeted supply of online ideological and political education has gradually formed a dynamic supply process through the coordination of target identification, content allocation, supply implementation, and effect feedback. As a crucial technical condition for platforms to organize information supply, algorithmic recommendation improves the feasibility of identifying supply targets, allocating supply content, and adjusting the supply process, and drives online ideological and political education to shift from relatively unified content distribution to more differentiated and targeted supply. Additionally, the operation of algorithmic recommendation is not inherently aligned with the educational goals of ideological and political education, bringing a series of realistic tension in terms of target confirmation, content orientation, and leading capacity. Specifically, the conflict between the uncertainty and generativity of educational recipients and the logic of active recommendation may lead to inaccurate identification of supply targets, omission of potential recipients, and rigidification of recipient structures. The mismatch between the intensification of individual preferences and the weakening of universal content provision tends to reduce the communication space for public-oriented content and reshape the value orientation and allocation logic of supplied content. Meanwhile, the contradiction between the expansion of platform power and the decline of educational dominance further undermines the decision-making foundation and implementation leadership of targeted supply. The algorithm-driven empowerment of the network ideological and political education for precise supply and the adjustment of the tension involved, technical fixes are insufficient. It is essential to accurately identify educational recipients through dynamic perception, strengthen the supply of public values with high-quality content, and safeguard the dominant role of educational subjects via collaborative governance, thereby promoting algorithmic recommendations to better serve the practical advancement of targeted supply in online ideological and political education.