Kalman Filtering is an algorithm that provides estimates of unknown variables by predicting a process's future state, correcting the prediction with new measurements, and minimizing the mean of the squared errors. It is widely used in control systems, navigation, and signal processing due to its ability to efficiently handle noisy data and uncertainties in dynamic systems.