Bayesian Time Series Models provide a probabilistic approach to time series analysis, incorporating prior beliefs and updating them with new data to improve predictions and uncertainty quantification. These models are particularly useful for handling non-stationary data, incorporating expert knowledge, and making robust forecasts in the presence of limited data or complex dynamics.