Model extrapolation is defined as estimating beyond a previously observed data range to establish the relationships between variables.
The main issue with extrapolation is that it is, at best, an educated guess. Since it has no data to support it, it’s generally not possible to claim that the observed relationships still hold. A relationship that looks linear in a given range might actually be non-linear when outside of range.