The users are classified by different membership degrees with fuzzy C-means clustering. A more accurate clustering effect has been obtained and the problem of low recommendation accuracy caused by hard clustering is solved. Aiming at the privacy leakage problem of recommendation algorithm, the Laplace noise is introduced into the fuzzy C-means clustering process, and the differential privacy protection based fuzzy C-means clustering recommendation is implemented. The experimental results show that the proposed algorithm can effectively improve the security of the recommended system with the good quality of the recommendation.