A Bayesian Filter is a statistical method used to classify data based on probabilities. It applies Bayes' Theorem, which calculates the likelihood of an event based on prior knowledge and new evidence. This technique is commonly used in applications like spam detection, where it evaluates the probability that an email is spam based on its content. The filter works by analyzing a set of training data to create a model of what constitutes spam versus non-spam. As new emails arrive, the filter updates its probabilities, improving its accuracy over time. This adaptive nature makes it effective for various classification tasks beyond just email filtering.