Shannon's Entropy is a concept from information theory introduced by Claude Shannon in 1948. It quantifies the amount of uncertainty or unpredictability in a set of possible outcomes. Higher entropy indicates more unpredictability, while lower entropy suggests more predictability. This measure helps in understanding how much information is produced when a message is received. In practical terms, Shannon's Entropy can be used to analyze data compression and communication systems. By calculating the entropy of a source, engineers can design more efficient coding schemes, ensuring that messages are transmitted with minimal redundancy while maintaining clarity and accuracy.