Step 1: 'Fastest' means the slowest growing function of the input size n, since that runs quickest for large n.
Step 2: Order the four choices by growth rate:
\[ O(\log n) < O(n \log n) < O(n^2) < O(2^n) \]
Step 3: Logarithmic growth is the smallest here. For example, at \( n = 1024 \), \( \log_2 n = 10 \), while \( n \log n \approx 10240 \), \( n^2 \approx 10^6 \), and \( 2^n \) is astronomically large.
Step 4: So \( O(\log n) \) is the best (fastest) complexity in the list.
Correct option: (B).