Least Squares is a mathematical method used to find the best-fitting line or curve for a set of data points. It minimizes the sum of the squares of the differences between the observed values and the values predicted by the model. This technique is widely used in statistics and data analysis to create linear regression models. The method was developed by the mathematician Carl Friedrich Gauss in the early 19th century. It is particularly useful in various fields, including economics, engineering, and the natural sciences, where it helps in making predictions and understanding relationships between variables.