Concept prerequisite relation learning (CPL) plays a crucial role in building educational applications such as learning path planning and educational question and answer system. Previous deep learning-based methods usually attempt to extract the relevant information for prerequisite relations between concepts from lengthy documents of educational data. However, the process of selecting evidence information that can infer prerequisite relations still lacks explicitness and interpretability. To explicitly select evidence information and utilize it to improve CPL, we propose a novel Evidence-Based method for Concept Prerequisite relation Learning (EBCPL). Firstly, we introduce a tailored evidence extraction method for educational data, which can explicitly extract evidence sentences from these documents. Secondly, we construct a relation extraction model with BiLSTM to infer prerequisite relations from the extracted evidence. Our experiments on multiple datasets demonstrate that the proposed method achieves state-of-the-art results in comparison with existing methods.