It is a very difficult problem in machine learning to learn uncertain knowledge automatically without prior domain knowledge. In this paper, a theory is developed to express, measure and process uncertain information and uncertain knowledge according to uncertainty measure of decision table and decision rule. Based on the Skowron’s default rule generation algorithm, a self-learning model and the method is developed to solve this problem. Simulation results illustrate the efficiency of this self-learning method.