Let $x ~ p(x)$ be I.I.D.
The posterior predictive distribution for the predicted observations based on the realised observations is
$p(x' | x) = \int d\theta p(x' | x, \theta) p(\theta | x) = \int d\theta p(x' | \theta) p(\theta | x)$
How does the second equality relies on the IID assumption?