The Bayesian approach is a statistical method that uses Bayes' theorem to update beliefs or estimates as new data or evidence is acquired. It involves the use of prior knowledge or beliefs about a situation, which are updated based on observed data to form a posterior distribution. This approach is used in various fields such as machine learning, genetics, finance, and healthcare to make predictions, infer unknown parameters, and quantify uncertainty in a systematic and principled way. The Bayesian approach allows for the incorporation of uncertainty and variability in the modeling process, making it a powerful tool for decision-making and inference.