Text classification is a branch of natural language processing (NLP) that involves automatically categorizing textual documents into predefined classes or categories based on their content. This process typically involves training a machine learning model on a labeled dataset of text documents to learn the patterns and characteristics of each class. Text classification is commonly used in various applications such as spam detection, sentiment analysis, topic categorization, and document classification. It plays a crucial role in organizing and managing large volumes of textual data, making it easier to search, retrieve, and analyze information.