Channel capacity is a technical concept from Shannon's information theory. It describes the maximum throughput of information a given channel can reliably carry. The textbook illustrates it with the checker-on-a-checkerboard analogy: if you ask randomly whether a checker is in any of 64 specific squares one by one, you may need up to 63 questions (inefficient). But by consistently halving the remaining possibilities (e.g., “Is it in the top half?”), you can identify the exact square in no more than 6 questions. This halving strategy is maximally efficient because it extracts the maximum information from each question, approaching the theoretical channel capacity. Channel capacity is also affected by noise — a noisy channel has lower effective capacity because some information is inevitably lost or corrupted in transmission. Modern data transmission rates (measured in bits per second or bandwidth) are a direct application of Shannon's channel capacity theory.