We use a simple recursive approach with base cases F(0) and F(1). While O(2^N) is slow, it demonstrates the core concept of recursion.

1. Base case: If n == 0, return 0.
2. Base case: If n == 1, return 1.
3. Recursive step: Return fib(n-1) + fib(n-2).

• Time Complexity: O(2^N).
• Space Complexity: O(N) (recursion stack).

def fib(n):
    if n == 0: return 0
    if n == 1: return 1
    return fib(n - 1) + fib(n - 2)

(Note: In real interviews, you should mention Memoization or Iterative approach to optimize this).