Times of nested algorithms in proofs of security
The equation $t'=t+n\cdot t_c$ is an estimation to put an upper limit on $t'$. It might be possible that an attacker $A'$ can use a different, more efficient algorithm. But since the attack will work with using $A$, there exists an attacker $A'$ with at most $t'$. This means it's actually not an equation, but an inequality $t' \leq t + n \cdot t_c$. And then the next step is just a standard transformation to get $t'  - n \cdot t_c \leq t$.

Edit:
Actually, this assumes that $A'$ only has to run $A$ once. There are also reductions which run $A$ multiple times. If you are only looking for asymptotical complexity, it doesn't change much, tho. Running a polynomial time algorithm polynomial many times is still polynomial overall.

Edit2:
Concerning your example, there are a couple of misunderstandings of of the these times. First, in a reduction we use $A$ mostly as a blackbox. We can observe the queries (e.g. if we assume an oracle for that, which can be accessed by both $A$ and $A'$). But we make no assumptions about these times. Saying that $A'$ takes 1 unit of time for a calculation and $A$ needing 1 unit of time for a query (and possibly some internal computations)  is an assumption about their correlation we should not make.

And then there is the question what we actually use from the attacker $A$. Usually we do not only use their queries, but their results. And that happens at the time $A$ is finished, which is $t$. Then $A'$ can do its final transformation of results or do some more complex computations, which is not necessarily instant (e.g. solving a large linear system or doing $k$ exponentiations, etc.). If you assume this to be instant, then $t=t'$ for exactly this attack. But that doesn't mean that this is the fastest attack (if you assume $A'$ to be the "best" attacker, $t'$ might be lower), or if those computations are not instant, then $t'$ might be greater.