The invention provides a non-negative matrix factorization face recognition method and system based on kernel machine learning, which comprises five steps. The invention has the following beneficial effects: the invention avoids the learning of the inaccurate pre-image matrix by directly learning two kernel matrices, Kwx and Kww, and avoids the derivation of the kernel function in the iterative formula by changing the learning object, so that there is no limit to the selection of kernel function and a general algorithm for any kernel function is obtained.