Channel capacity becomes operational through Shannon's noisy-channel coding theorem.

For a channel model with capacity $C$ under the standard coding-theorem assumptions, communication at any rate

$$R<C$$

can, in principle, be performed with arbitrarily small probability of decoding error by using sufficiently long and suitably designed codes.

Conversely, rates above capacity cannot achieve arbitrarily reliable communication under the same channel constraints.

The theorem does not provide one universal practical code and does not say that finite block lengths eliminate all errors. It establishes an asymptotic boundary between achievable and unachievable rates.

Reliability is obtained by adding structured redundancy across many channel uses. The receiver uses the whole received codeword to infer which valid transmitted codeword was most likely.

Capacity tells how much information the channel can fundamentally support; coding determines how closely a practical system approaches that limit.