Text Classification is a machine learning technique that automatically assigns predefined categories or labels to text documents based on their content. It's a supervised learning approach that uses labeled training data to learn patterns and classify new, unseen text.

Common applications include:

• Spam Detection: Filtering unwanted emails
• Topic Categorization: Organizing documents by subject
• Content Moderation: Identifying inappropriate content
• Intent Classification: Understanding user requests in chatbots
• Document Routing: Automatically directing documents to appropriate departments

Text classification algorithms range from traditional methods like Naive Bayes and Support Vector Machines to modern deep learning approaches using neural networks and transformer models.