I would like to address a legitimate concern from Doofenshmert, who commented on 75064's answer (however please excuse my choice of $k$ for the Fourier coefficients instead of the $k$ of the question for the regularity, I only realised mid-writing. I'm using $p$ for that instead).
As noticed by Doofenshmert, he issue with simply taking antiderivatives of a "random" approximation of $f$ by a trigonometric polynomial is the apparition of a non-trigonometric polynomial term, which should have appeared at the first antiderivative but will inevitably arrive on the second one if $b \neq 0$ in 75064's construction.
75064's account hasn't been logged in since 10 years ago though, looking at their profile page, hence my decision to write an answer instead of just commenting.
I think a good way to correct this is to refine the selction of said approximation.
Let $c_k(f)$ be the $k$-th Fourier coefficient of $f$. Then we know (by successive integrations by parts) that $c_k(f') = ik c_k(f)$, so that:
$$\left(c_k(f) e^{ikx}\right)'(x_0) = c_k(f) ik e^{ikx_0} = c_k(f') e^{ikx_0}$$
Moreover, by Fejér's theorem, we know that, if $f$ is continuous, $(\sigma_N(f))_{N \geq 0}$ converges uniformly to $f$ as $N \to \infty$, where $\sigma_N(f)$ is defined by, for $N \in \mathbb{N}$:
$$\sigma_N(f) : x \mapsto \frac{1}{N+1}\sum_{n = 0}^N \sum_{k = -n}^{n} c_k(f) e^{ikx}$$
We can rewrite $\sigma_N(f)$ by swapping the indices, although it's not really required for this answer:
$$\sigma_N(f)(x) = \frac{1}{N+1}\sum_{k = -N}^N \sum_{n = |k|}^{N} c_k(f) e^{ikx} = \sum_{k = -N}^N \frac{N - |k| + 1}{N + 1} c_k(f) e^{ikx}$$
Thus, thanks to our previous observation, we can see that:
$$\sigma_N(f') = (\sigma_N(f))'$$
which means that not only does $\sigma_N(f)$ converge uniformly to $f$, but all its derivatives also do to the corresponding derivatives of $f$ (by simple induction), which means that $(\sigma_N(f))_N$ converges to $f$ in $\mathcal{C}^p(\mathbb{S}^1)$ if $f \in \mathcal{C}^p(\mathbb{S}^1)$.