Captum is an extensible library that provides general-purpose implementations for model interpretability in PyTorch. It aims to demystify complex machine learning models by offering several algorithms to analyze and understand model predictions. Captum includes a variety of methods such as feature ablation, integrated gradients, and others, which help researchers and developers to comprehend and improve their models.