Is a common approach to calibration reasonable?

"Model Calibration" article in Encyclopedia of Quantitative Finance states that

. . . a common approach for selecting a pricing measure $\mathbb{Q}$ is to choose, given a set of liquidly traded derivatives with (discounted) terminal payoffs $(H^i)_{i \in I}$ and market prices $(C_i)_{i \in I}$, a pricing measure $\mathbb{Q}$ compatible with the observed market prices

where $\mathbb{Q}$ denotes

a probability measure on the set $\Omega$ of possible trajectories $(S_t)_{ t \in [0,T ]}$ of the underlying asset such that the asset price $\frac{S_t}{N_t}$ discounted by the numeraire $N_t$ is a martingale.

But we know that market prices $(C_i)_{i \in I}$ are generated by fallible human beings! Each of them has rather limited knowledge about "possible trajectories $(S_t)_{ t \in [0,T ]}$ of the underlying asset". Otherwise they wouldn't need the model we are trying to calibrate, would they?

So The Calibration Process receives some prices $(C_i)_{i \in I}$, some arbitrarily choosen mathematical model (i.e. Heston) and produces as an output the calibrated model which supposedly able to give us predictions about the future $(S_t)_{ t \in [0,T ]}$

Why do we believe that The Calibration Process is different from GIGO process?