In order to improve the instability of handwritten character pattern caused by different writing styles, a novel handwritten numeral character recognition approach based on manifold learning is proposed in this paper.Based on non-supervised manifold learning,a supervised information is induced to the algorithm to ensure the map from high dimension to low dimension to retain some manifold structures and also to seperate different kinds of manifolds. By proposed method,Supervised Locally Linear Embedding (SLLE) algorithm is used to reduce the dimensionality of input feature.Then, the reduced feature is classified by simple classifier.Finally,the proposed algorithm is tested on the characters in MINST character database. The experimental results demonstrate that the method can effectively improve the recognition rate to 93.27% and can provide a new approach to the research of handwritten numeral character recognition.