Data bias happens when the examples a model learns from don't fairly represent everyone or everything — so the model ends up being unfair too.
Imagine it like this: If you practiced free throws only on a hoop set too low, you'd get amazing at that hoop, but struggle on a regular one. Your training wasn't a fair representation of the real challenge — that's bias.
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