Big Θ (Theta) notation is a mathematical concept used in computer science to describe the asymptotic behavior of algorithms. It provides a tight bound on the running time or space requirements of an algorithm, indicating that the algorithm's performance grows at the same rate as a given function. This means that for sufficiently large inputs, the algorithm's running time will be both upper and lower bounded by the same function. In formal terms, an algorithm is said to be in Θ(f(n)) if there are positive constants c₁, c₂, and n₀ such that for all n ≥ n₀, c₁ * f(n) ≤ T(n) ≤ c₂ * f(n), where T(n) is the running time of the algorithm and f(n) is a function that describes its growth rate. This notation helps in comparing the efficiency of different algorithms, making it easier to analyze their performance in relation to input size.