Algorithmic information theory is a branch of computer science and mathematics that studies the complexity of information. It focuses on quantifying how much information is contained in a data set and how efficiently that information can be represented. This theory combines concepts from information theory and computability theory to analyze the limits of data compression and the randomness of sequences. A key concept in algorithmic information theory is the Kolmogorov complexity, which measures the length of the shortest possible description of an object, such as a string of text. This helps determine how much information is needed to recreate the original data, providing insights into data compression and the nature of randomness in information.