Shannon Entropy is a measure of uncertainty or randomness in a set of possible outcomes. Developed by Claude Shannon, it quantifies the amount of information produced when an event occurs. Higher entropy indicates more unpredictability, while lower entropy suggests more predictability in the outcomes. In practical terms, Shannon Entropy is used in various fields, including information theory, cryptography, and data compression. It helps determine the efficiency of encoding messages and the security of communication systems. By understanding entropy, we can better analyze and manage information in complex systems.