Each coefficient is the expected change in the target when that feature rises by one unit and the others stay fixed. The intercept is the prediction when every feature equals zero. That is often a meaningless point, because zero may sit far outside the observed data.
Units drive everything. A coefficient of 3200 on bedrooms means 3200 more dollars per extra bedroom. You cannot compare raw coefficients across features, because a variable measured in millimetres earns a tiny number. Standardize the features first if you want to rank them by influence.
The phrase "holding the others fixed" is where readings go wrong. When two features move together in reality, nobody can hold one still, so the number is not a causal effect. Signs can even flip when you add or remove a related feature. Always report a coefficient alongside the exact feature set it was fitted with.
Rewriting in plainer words…
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