Linear Quadratic Estimation, commonly known as the Kalman Filter, is an algorithm that uses a series of measurements observed over time, containing 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, navigation, and signal processing for its ability to efficiently process noisy data and provide real-time updates.