The "Laplace Box" is a conceptual tool used in statistics and probability theory, named after the mathematician Pierre-Simon Laplace. It helps in understanding how to update beliefs based on new evidence. The box represents a scenario where you can draw balls of different colors, and the outcome helps refine your predictions about the likelihood of drawing a specific color in the future. In practical applications, the Laplace Box illustrates the principle of Bayesian inference, where prior knowledge is combined with new data to improve decision-making. This method is widely used in fields like machine learning, finance, and scientific research to make informed predictions.