Entropy Encoding is a data compression technique that reduces the size of data by assigning shorter codes to more frequently occurring symbols and longer codes to less frequent ones. This method takes advantage of the statistical properties of the data, allowing for efficient storage and transmission. Common examples of Entropy Encoding include Huffman Coding and Arithmetic Coding. These algorithms analyze the input data to create a codebook, which maps each symbol to a unique binary code based on its frequency. By using this approach, Entropy Encoding can significantly decrease the amount of space needed to store information.