Kalman Filter is a mathematical algorithm used to estimate the state of a system when the measurements are noisy or incomplete. It is widely used in control systems, robotics, and navigation applications. The algorithm works by predicting the state of the system based on past measurements and then updating the prediction with the current measurement to get an optimized estimate. Kalman Filter requires a good understanding of system dynamics, probability theory, and linear algebra to implement and use effectively.