Aiming at insufficient user fairness in UAV-assisted mobile edge computing systems, this study proposes a user fairness-oriented 3D deployment and unloading optimization algorithm. The algorithm comprehensively considers the effects of user matching, 3D UAV deployment, computing resource allocation, and unloading factors on the total system delay and user fairness. Meanwhile, a multivariate optimization problem is established to minimize the total system delay, and a two-stage joint optimization algorithm is put forward for this problem. In the first stage, a clustering algorithm with balanced constraints is adopted to solve the problem of user matching and horizontal UAV deployment. In the second stage, the convex optimization algorithm is utilized to iteratively solve the UAV altitude deployment, resource allocation, and optimization problems of unloading factors. The experimental results show that the proposed algorithm has better performance than the four benchmark algorithms in both total system latency and user fairness.