A Kalman Filter is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, to produce estimates of unknown variables that tend to be more precise than those based on a single measurement alone. It is widely used in control systems, robotics, and navigation to predict the state of a dynamic system in real-time by recursively updating estimates with new data.