Asymptotic notation is a mathematical concept used in computer science to describe the behavior of algorithms as their input size grows. It provides a way to express the efficiency of an algorithm in terms of time or space complexity, allowing for comparisons between different algorithms. The most common types of asymptotic notation are Big O, Big Theta, and Big Omega, each representing upper, tight, and lower bounds, respectively. These notations help in analyzing how an algorithm performs under large inputs, abstracting away constant factors and lower-order terms. By focusing on the dominant term, asymptotic notation simplifies the understanding of an algorithm's efficiency, making it easier to predict its performance in practical applications.