Jensen's Inequality is a mathematical concept that relates to the behavior of convex functions. It states that for any convex function, the value of the function at the average of a set of points is less than or equal to the average of the function values at those points. This means that if you take a weighted average of inputs, applying the function afterward will yield a result that is less than or equal to applying the function first and then averaging. This inequality is useful in various fields, including economics, finance, and statistics, as it helps in understanding how averages behave under different transformations. It highlights the importance of the shape of functions and can be applied to optimize decisions and analyze risk.